Field of the Technology
The invention relates to the field of OCT angiography, specifically an apparatus and method for an automatic three-dimensional segmentation method for OCT and Doppler OCT angiography
Description of the Prior Art
Most retinal diseases are closely related to vasculopathy, such as diabetic retinopathy, retinal vascular occlusive disease, and choroidal neovascularization. Fundus fluorescein angiography (FFA) is widely used in clinical practice and is the gold standard for vascular imaging of the retina and choroid. However, FFA is an invasive procedure with an associated risk of complications which limits clinical applications. In addition, FFA can only provide two-dimensional images of the fundus, and the deeper capillary network may be not visualized well by FFA.
Optical coherence tomography (OCT) is a non-invasive, high-resolution biomedical imaging technology that can provide three-dimensional images of the fundus. Doppler OCT (D-OCT) is a functional extension of OCT which can image not only structure but also blood flow. Compared to the absolute value of flow velocity, the microvascular networks in the retina are also important for diagnosing retinal diseases. A number of methods have been developed to visualize the microvascular networks. A phase-resolved Doppler variance method was first used to map vessels in human skin and within the brain. Since then, it has been used in imaging retinal flow. Yasuno et al. and Wang et al. used a modified Hilbert transform to achieve high resolution images of blood flow. Several extensions of Doppler OCT based on amplitude variance have also demonstrated capabilities of microvascular imaging which are not sensitive to phase noise artifacts, including speckle variance, correlation mapping, split-spectrum amplitude-decorrelation angiography, and intensity based Doppler variance (IBDV). Compared with phase-resolved methods, amplitude variance methods do not depend on phase stability. The IBDV method has been demonstrated in a phase instable situation, and imaging of the human choroidal blood vessel network was also achieved.
Compared with FFA which only shows two-dimensional images of the fundus, OCT can provide three dimensional structure of the fundus. The vascular morphology of intra-retinal layers can be obtained by combining OCT angiography and three dimensional segmentation of intra-retinal layers. It may allow earlier diagnosis and more precise monitoring of some retinal diseases. There are several approaches that have successfully segmented intra-retinal layers in two dimensional images, such as the active contour model, Dijkstra algorithm and dynamic programming. The three dimensional surfaces of the retina can be obtained by applying these two dimensional based algorithms on each image independently. Compared with two dimensional-based methods, three dimensional-based segmentation methods can make full use of the information from neighboring B-scans and help improve the accuracy and robustness of the algorithm. A graph cut-based segmentation method was proposed for simultaneous segmentation of multiple three dimensional surfaces in macula and optic nerve head. However, the minimum cut graph algorithm is computationally expensive which usually requires minutes to complete a three dimensional data segmentation. Cheng et al, proposed a fast three dimensional dynamic programming expansion method for vessel boundary detection on MRI sequences. Efficiency was significantly improved with good robustness, and this method can be used in retinal boundary detection.